Triple

T34777233
Position Surface form Disambiguated ID Type / Status
Subject territory of the Republic of Slovenia E1002537 entity
Predicate containsCity P294 FINISHED
Object Loška Dolina
Loška Dolina is a municipality in southern Slovenia known for its karst landscape, forests, and traditional rural settlements near the Snežnik plateau.
E2118004 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Loška Dolina | Statement: [territory of the Republic of Slovenia, containsCity, Loška Dolina]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Loška Dolina
Triple: [territory of the Republic of Slovenia, containsCity, Loška Dolina]
Generated description
Loška Dolina is a municipality in southern Slovenia known for its karst landscape, forests, and traditional rural settlements near the Snežnik plateau.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76db30a108190bb57ca95b873e5bb completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f77a3e846c8190a4623b0666a5b90e completed May 3, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37a89e7be88190b295f37f0bbd5edf completed June 21, 2026, 9:02 a.m.
NEDg Description generation batch_6a37a976d678819085e155f8799a1673 completed June 21, 2026, 9:05 a.m.
NED2 Entity disambiguation (via description) batch_6a37aa2b1fd08190a7e216e6c6402e48 completed June 21, 2026, 9:08 a.m.
Created at: May 3, 2026, 3:59 p.m.